Data can be described as the new gold that’s leading the fourth industrial revolution. In fact, it’s one of the most important assets a company could have to drive future performance and make better business decisions.
Over the last few years, big data has matured and it’s now a little easier to extract valuable insights from enormous oceans of information. This has had a significant impact on multiple industries from logistics to retail to technology.
However, if you’re not a data scientist, you might be wondering what exactly these “insights” are and how it can enhance business processes.
So to help you get a better idea, I have put together some real-world examples of how big data is already changing the way we work and do business.
Amazon was one of the first to leverage data to drive sales and make better business decisions. From the time of its inception, the company has used data to suggest products based on similarities and collaborative filtering.
With over 152 million customers on their massive database, Amazon has mastered the art of making recommendations based on historical data and customer click-stream data to drive sales.
The company is also leveraging big data to improve their service by rapidly providing customer data to the customer service representative to accelerate the whole process. When customers don’t have to provide all their information during each interaction, it really makes a world of a difference.
The valuable insights extracted from big data analytics is also used to track, monitor, and secure over 1.5 billion items from its online retail platform and stored in over 200 fulfillment centers across the planet.
Furthermore, the company is also leveraging big data to become more competitive in various market segments.
Like Amazon, American Express is also engaging in big data analytics to better understand and predict consumer behavior. For about eight years the company has been extracting valuable insights from a database of over 100 million credit card holders to deliver innovative products in payments and commerce.
American Express derives insights by looking at historical transactions against over 100 variables. This approach allowed the company to develop and implement highly sophisticated predictive models that replaced (traditional) intelligence-based hindsight reporting.
As a result, the company is now able to make more accurate forecasts when it comes to customer loyalty. Big data also plays an important role in fraud detection and new customer acquisition.
The California-based company Equinix provides insurance companies a platform that simplifies data sharing among all stakeholders. In fact, they make it easy to seamlessly connect the global insurance market to enhance the performance of risk modeling.
For example, these risk models can help insurance companies better understand the behavior of drivers and reward those who have fewer automobile accidents by significantly reducing the cost of their premiums. The same approach can also be used to build risk management models for natural disasters.
Fido Solutions Limited (FIDO)
FIDO, a financial institution based in Accra, Ghana provides short-term loans to its customers who can apply for them from mobile devices. It’s a service that offers credit decisions within minutes based on data, negating the need for collateral and/or guarantors.
We know this company well as Intersog helped them completely replace their old legacy software systems and create a central hub. By doing this, FIDO is now able to leverage a massive amount of data generated from multiple sources.
When data is stored in multiple databases, it can quickly become a challenge to engage in big data analytics. But with our help, FIDO can aggregate all the data in one place to engage in predictive analytics and provide the customers with a great service.
The global coffee giant Starbucks has over 25,000 stores across the planet and conducts 90 million transactions a week. That much activity will generate an enormous amount of data that can be leveraged to make better sales and business decisions.
Known for being at the cutting edge of new technologies, the company was one of the first to embrace big data. So what exactly did they do? Well, to start, they actually collected even more data!
A few years ago, the company launched their rewards program and mobile app to get to know their customers even better. The rewards program has 13 million active users while the mobile app has over 17 million downloads.
The data collected helped the company to achieve the following:
- Offer their customers complimentary products that go with their coffee (based on things like the weather or special holidays)
- Better target their customers in their personalized marketing initiatives
- Offer a personalized Starbucks experience at any location around the world
- Menu updates
Big data was also used to determine the sites of new store locations. They did this because data analytics had a significant impact on their chances of succeeding.
So if you have ever wondered why a few Starbucks stores are located close to each other, you can bet a data scientist was behind that decision.